Method and apparatus for rolled fingerprint capture

ABSTRACT

A method and apparatus for rolled fingerprint capture is described. The start of a fingerprint roll is detected. A plurality of fingerprint image frames are captured. A centroid window corresponding to each of the plurality of captured fingerprint image frames is determined. Pixels of each determined centroid window are knitted into a composite fingerprint image. The end of the fingerprint roll is detected.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention is directed to the field of rolled fingerprintcapture, and more specifically, to capturing and combining multiplefingerprint images to generate an overall rolled fingerprint image.

2. Related Art

A rolled fingerprint scanner is a device used to capture rolledfingerprint images. The scanner captures the image of a user'sfingerprint as the user rolls a finger across an image capturingsurface. Multiple fingerprint images may be captured by the scanner asthe finger is rolled. These images may be combined to form a compositerolled fingerprint image. A computer system may be used to create thecomposite rolled fingerprint image. Fingerprint images captured by adigital camera are generally comprised of pixels. Combining the pixelsof fingerprint images into a composite fingerprint image is commonlyreferred to as pixel “knitting.”

The captured composite rolled fingerprint image may be used to identifythe user. Fingerprint biometrics are largely regarded as an accuratemethod of identification and verification. A biometric is a unique,measurable characteristic or trait of a human being for automaticallyrecognizing or verifying identity. See, e.g., Roethenbaugh, G. Ed.,Biometrics Explained (International Computer Security Association:Carlisle, Pa. 1998), pages 1–34, which is herein incorporated byreference in its entirety.

Capturing rolled fingerprints using a fingerprint scanner coupled to acomputer may be accomplished in a number of ways. Many currenttechnologies implement a guide to assist the user. These guidesprimarily come in two varieties. The first type includes a guide locatedon the fingerprint scanner itself. This type may include guides such aslight emitting diodes (LEDs) that move across the top and/or bottom ofthe scanner. The user is instructed to roll the finger at the same speedas the LEDs moving across the scanner. In doing so, the user inevitablygoes too fast or too slow, resulting in poor quality images. The secondtype includes a guide located on a computer screen. Again, the user mustmatch the speed of the guide, with the accompanying disadvantages. Whatis needed is a method and apparatus for capturing rolled fingerprintimages without the requirement of a guide.

Current devices exist for collecting rolled fingerprint images. Forinstance, U.S. Pat. No. 4,933,976 describes using the statisticalvariance between successive fingerprint image “slices” to knit togethera composite fingerprint image. This patent also describes techniques foraveraging successive slices into the composite image. These techniqueshave the disadvantage of less than desirable image contrast. What isneeded is a method and apparatus for capturing rolled fingerprint imageswith improved contrast imaging.

SUMMARY OF THE INVENTION

The present invention is directed to a method and apparatus for rolledfingerprint capture. The invention detects the start of a fingerprintroll. A plurality of fingerprint image frames are captured. A centroidwindow corresponding to each of the plurality of captured fingerprintimage frames is determined. Pixels of each determined centroid windoware knitted into a composite fingerprint image. The end of thefingerprint roll is detected.

In an embodiment, a pixel intensity difference count percentage valuebetween a current fingerprint image frame and a previous fingerprintimage frame is generated. Whether the generated pixel intensitydifference count percentage value is greater than a start rollsensitivity threshold percentage value is determined.

Furthermore, in embodiments, a pixel window in a captured fingerprintimage frame is determined. A leading edge column and a trailing edgecolumn of a fingerprint image in the corresponding generated pixelwindow are found. A centroid window in the captured fingerprint imageframe bounded by the leading edge column found and the trailing edgecolumn found is generated.

The present invention further provides a novel algorithm for knittingfingerprint images together. Instead of averaging successive pixels, thealgorithm of the present invention compares an existing pixel value to acaptured potential new pixel value. New pixel values are only knitted ifthey are darker than the existing pixel value. The resultant image ofthe present invention has a much higher contrast than images that havebeen averaged or smoothed by previous techniques. In an embodiment, theinvention compares the intensity of each pixel of the determinedcentroid window to the intensity of a corresponding pixel of a compositefingerprint image. The pixel of the composite fingerprint image isreplaced with the corresponding pixel of the determined centroid windowif the pixel of the determined centroid window is darker than thecorresponding pixel of the composite fingerprint image.

Furthermore, existing fingerprint capturing devices require actuating afoot pedal to begin the capture process. The present invention requiresno such activation. The algorithm of the present invention can beinstantiated through a variety of software/hardware means (e.g. mouseclick, voice command, etc.).

According to a further feature, the present invention provides a rolledfingerprint capture algorithm that can operate in either of two modes:guided and unguided. The present invention may provide the guidedfeature in order to support legacy systems; however, the preferred modeof operation is the unguided mode. Capturing rolled fingerprints withouta guide has advantages. These advantages include decreased fingerprintscanner device complexity (no guide components required), and no need totrain users to follow the speed of the guide.

Further embodiments, features, and advantages of the present inventions,as well as the structure and operation of the various embodiments of thepresent invention, are described in detail below with reference to theaccompanying drawings.

BRIEF DESCRIPTION OF THE FIGURES

The accompanying drawings, which are incorporated herein and form a partof the specification, illustrate the present invention and, togetherwith the description, further serve to explain the principles of theinvention and to enable a person skilled in the pertinent art to makeand use the invention. In the drawings:

FIG. 1 illustrates an example high level block diagram of a preferredembodiment of the present invention.

FIG. 2A illustrates a detailed block diagram of an embodiment of arolled fingerprint capture module of the present invention.

FIG. 2B illustrates a detailed block diagram of an embodiment of afingerprint image format module.

FIGS. 2C–2E illustrate example embodiments of a fingerprint rolldetector module.

FIGS. 3A–3G show flowcharts providing detailed operational steps of anexample embodiment of the present invention.

FIG. 4 shows an example captured image frame.

FIG. 5 shows an example captured fingerprint image frame with afingerprint image present.

FIG. 6 shows an example captured fingerprint image frame with afingerprint image and a pixel window present.

FIG. 7A shows a more detailed example pixel window.

FIG. 7B shows a histogram related to the example pixel window shown inFIG. 7A.

FIG. 8 shows an example of pixel knitting for an example segment of acomposite fingerprint image.

FIG. 9 shows an example of an overall rolled fingerprint image,displayed in a rolled fingerprint display panel.

FIG. 10 shows an example computer system for implementing the presentinvention

The present invention will now be described with reference to theaccompanying drawings. In the drawings, like reference numbers indicateidentical or functionally similar elements. Additionally, the left-mostdigit(s) of a reference number identifies the drawing in which thereference number first appears.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Overview and Terminology

The present invention is directed to a method and apparatus for rolledfingerprint capture. The invention detects the start and end of afingerprint roll. One or more fingerprint image frames are captured. Acentroid window corresponding to each of the captured fingerprint imageframes is determined. Pixels of each determined centroid window areknitted into a composite fingerprint image. The composite fingerprintimage represents an image of a complete fingerprint roll.

To more clearly delineate the present invention, an effort is madethroughout the specification to adhere to the following term definitionsas consistently as possible.

“USB” port means a universal serial bus port.

The term “fingerprint image frame” means the image data obtained in asingle sample of a fingerprint image area of a fingerprint scanner,including fingerprint image data. A fingerprint image frame has acertain width and height in terms of image pixels, determined by thefingerprint scanner and the application.

The terms “centroid” or “fingerprint centroid” means the pixels of afingerprint image frame that comprise a fingerprint.

The term “centroid window” means an area of pixels substantiallysurrounding and including a fingerprint centroid. This area of pixelscan be any shape, including but not limited to rectangular, Square, orother shape.

Example Rolled Fingerprint Capture Environment

Structural implementations for rolled fingerprint capture according tothe present invention are described at a high-level and at a moredetailed level. These structural implementations are described hereinfor illustrative purposes, and are not limiting. In particular, rolledfingerprint capture as described in this section can be achieved usingany number of structural implementations, including hardware, firmware,software, or any combination thereof.

FIG. 1 illustrates an example high level block diagram of a preferredembodiment of the present invention. Rolled fingerprint captureapparatus 100 includes a fingerprint scanner 102, a computer system 104,and a display 106.

Fingerprint scanner 102 captures a user's fingerprint. Fingerprintscanner 102 may be any suitable type of fingerprint scanner, known topersons skilled in the relevant art(s). For example, fingerprint scanner102 may be a Cross Match Technologies Verifier Model 290 FingerprintCapture Device. Fingerprint scanner 102 includes a fingerprint-imagecapturing area or surface, where a user may apply a finger, and roll theapplied finger across the fingerprint capturing area or surface.Fingerprint scanner 102 periodically samples the fingerprint imagecapturing area, and outputs captured image data from the fingerprintimage capturing area. Fingerprint scanner 102 is coupled to computersystem 104.

Fingerprint scanner 102 may be coupled to computer system 104 in anynumber of ways. Some of the more common methods include coupling by aframe grabber, a USB port, and a parallel port. Other methods ofcoupling fingerprint scanner 102 to computer system 104 will be known bypersons skilled in the relevant art(s), and are within the scope of thepresent invention.

Computer system 104 receives captured fingerprint image data fromfingerprint scanner 102. Computer system 104 may provide a samplingsignal to fingerprint scanner 102 that causes fingerprint scanner 102 tocapture fingerprint image frames. Computer system 104 combines thecaptured fingerprint image data/frames into composite or overallfingerprint images. Further details of combining captured fingerprintimage frames into composite or overall fingerprint images is providedbelow.

Computer system 104 may comprise a personal computer, a mainframecomputer, one or more processors, specialized hardware, software,firmware, or any combination thereof, and/or any other device capable ofprocessing the captured fingerprint image data as described herein.Computer system 104 may comprise a hard drive, a floppy drive, memory, akeyboard, a computer mouse, and any additional peripherals known toperson(s) skilled in the relevant art(s), as necessary. Computer system104 allows a user to initiate and terminate a rolled fingerprint capturesession. Computer system 104 also allows a user to modify rolledfingerprint capture session options and parameters, as further describedbelow.

Computer system 104 may be optionally coupled to a communicationsinterface signal 110. Computer system 104 may output fingerprint imagedata, or any other related data, on optional communications interfacesignal 110. Optional communications interface signal 110 may interfacethe data with a network, the Internet, or any other data communicationmedium known to persons skilled in the relevant art(s). Through thiscommunication medium, the data may be routed to any fingerprint imagedata receiving entity of interest, as would be known to persons skilledin the relevant art(s). For example, such entities may include thepolice and other law enforcement agencies. Computer system 104 maycomprise a modem, or any other communications interface, as would beknown to persons skilled in the relevant art(s), to transmit and receivedata on optional communications interface signal 110.

Display 106 is coupled to computer system 104. Computer system 104outputs fingerprint image data, including individual frames andcomposite rolled fingerprint images, to display 106. Any related rolledfingerprint capture session options, parameters, or outputs of interest,may be output to display 106. Display 106 displays the receivedfingerprint image data and related rolled fingerprint capture sessionoptions, parameters, and outputs. Display 106 may include a computermonitor, or any other applicable display known to persons skilled in therelevant art(s) from the teachings herein.

Embodiments for computer system 104 are further described below withrespect to FIG. 10.

As shown in FIG. 1, computer system 104 comprises a rolled fingerprintcapture module 108. Rolled fingerprint capture module 108 detects thestart and stop of fingerprint rolls on fingerprint scanner 102.Furthermore, rolled fingerprint capture module 108 combines capturedrolled fingerprint image frames into composite rolled fingerprintimages. Further structural and operational detail of rolled fingerprintcapture module 108 is provided below. Rolled fingerprint capture module108 may be implemented in hardware, firmware, software, or a combinationthereof. Other structural embodiments for rolled fingerprint capturemodule 108 will be apparent to persons skilled in the relevant art(s)based on the discussion contained herein.

The present invention is described in terms of the exemplary environmentshown in FIG. 1. However, the present invention can be used in anyrolled fingerprint capture environment where a fingerprint scanner thatcaptures rolled fingerprint images is interfaced with a display thatdisplays fingerprint images. For instance, in an embodiment, fingerprintscanner 102 and/or display 106 may comprise rolled fingerprint capturemodule 108. In such an embodiment, fingerprint scanner 102 may becoupled to display 106, and computer system 104 may not be necessary inpart or in its entirety. Such embodiments are within the scope of thepresent invention.

Description in these terms is provided for convenience only. It is notintended that the invention be limited to application in this exampleenvironment. In fact, after reading the following description, it willbecome apparent to a person skilled in the relevant art how to implementthe invention in alternative environments known now or developed in thefuture.

Rolled Fingerprint Capture Module Embodiments

Implementations for a rolled fingerprint capture module 108 aredescribed at a high-level and at a more detailed level. These structuralimplementations are described herein for illustrative purposes, and arenot limiting. In particular, the rolled fingerprint capture module 108as described in this section can be achieved using any number ofstructural implementations, including hardware, firmware, software, orany combination thereof. The details of such structural implementationswill be apparent to persons skilled in the relevant art(s) based on theteachings contained herein.

FIG. 2A illustrates a more detailed block diagram of an embodiment of arolled fingerprint capture module 108 of the present invention. Rolledfingerprint capture module 108 includes a fingerprint frame capturemodule 202, a fingerprint image format module 204, and a fingerprintimage display module 206.

Fingerprint frame capture module 202 receives a fingerprint scanner datasignal 208. Fingerprint scanner data signal 208 comprises fingerprintimage frame data captured by fingerprint scanner 102. In an embodiment,fingerprint frame capture module 202 allocates memory to hold afingerprint frame, initiates transfer of the frame from the fingerprintscanner 102, and arranges the pixels for subsequent analysis.Fingerprint frame capture module 202 outputs a captured fingerprintimage frame data signal 210. Captured fingerprint image frame datasignal 210 comprises fingerprint image frame data, preferably in theform of digitized image pixels. For instance, fingerprint image framedata signal 210 may comprise a series of slices of fingerprint imageframe data, where each slice is a vertical line of image pixels.

Fingerprint image format module 204 receives captured fingerprint imageframe data signal 210. Fingerprint image format module 204 detects thestart and stop of fingerprint rolls using captured fingerprint imageframe data signal 210. Furthermore, fingerprint image format module 204combines captured rolled fingerprint image frames into composite rolledfingerprint images. Further structural and operational embodiments ofrolled fingerprint capture module 108 are provided below. Fingerprintimage format module 204 outputs a composite fingerprint image datasignal 212. Composite fingerprint image data signal 212 comprisesfingerprint image data, such as a single rolled fingerprint image frame,or any combination of one or more rolled fingerprint image frames,including a complete rolled fingerprint image.

Fingerprint image display module 206 receives composite fingerprintimage data signal 212. Fingerprint image display module 206 provides anydisplay formatting and any display drivers necessary for displayingfingerprint images on-display 106. In a preferred embodiment,fingerprint image display module 206 formats the fingerprint imagepixels into a Windows Device Independent Bitmap (DIB). This is apreferred image format used by the Microsoft Windows Graphical DeviceInterface (GDI) Engine. Fingerprint image display module 206 outputs afingerprint image display signal 214, preferably in DIB format.

FIG. 2B illustrates a more detailed block diagram of an embodiment offingerprint image format module 204. Fingerprint image format module 204includes fingerprint roll detector module 216, centroid windowdeterminer module 218, and pixel knitting module 220.

Fingerprint roll detector module 216 detects when a fingerprint roll hasstarted, and detects when the fingerprint roll has stopped. FIG. 2Cshows an example embodiment of fingerprint roll detector module 216.Fingerprint roll detector module 216 includes a fingerprint roll startdetector module 222 and a fingerprint roll stop detector module 224.Fingerprint roll start detector module 222 detects the start of afingerprint roll. Fingerprint roll stop detector module 224 detects thestop of a fingerprint roll. In the example embodiment of FIG. 2C,fingerprint roll start detector module 222 and fingerprint roll stopdetector module 224 do not contain overlapping structure. In otherembodiments, fingerprint roll start detector module 222 and fingerprintroll stop detector module 224 share structure. In an alternativeembodiment shown in FIG. 2D, fingerprint roll start detector module 222and fingerprint roll stop detector module 224 contain common structure.The common structure provides advantages, such as requiring a lesseramount of hardware, software, and/or firmware. In an example alternativeembodiment shown in FIG. 2E, fingerprint roll start detector module 222and fingerprint roll stop detector module 224 share a common framedifference detector module 226. Frame difference detector module 226detects differences between consecutively captured fingerprint imageframes. Embodiments of fingerprint roll start detector module 222,fingerprint roll stop detector module 224, and frame difference detectormodule 226 are described in greater detail below.

Referring back to FIG. 2B, centroid window determiner module 218determines the portion of a captured fingerprint image frame where thefinger currently is located. This portion of a fingerprint image frameis called a centroid window. Embodiments of this module are described infurther detail below.

Pixel knitting module 220 knits together the relevant portions ofcentroid windows to create composite rolled fingerprint images.Embodiments of this module are described in further detail below.

The embodiments described above are provided for purposes ofillustration. These embodiments are not intended to limit the invention.Alternate embodiments, differing slightly or substantially from thosedescribed herein, will be apparent to persons skilled in the relevantart(s) based on the teachings contained herein.

Operation

Exemplary operational and/or structural implementations related to thestructure(s), and/or embodiments described above are presented in thissection (and its subsections). These components and methods arepresented herein for purposes of illustration, and not limitation. Theinvention is not limited to the particular examples of components andmethods described herein. Alternatives (including equivalents,extensions, variations, deviations, etc., of those described herein)will be apparent to persons skilled in the relevant art(s) based on theteachings contained herein. Such alternatives fall within the scope andspirit of the present invention.

FIG. 3A shows a flowchart providing detailed operational steps of anexample embodiment of the present invention. The steps of FIG. 3A may beimplemented in hardware, firmware, software, or a combination thereof.For instance, the steps of FIG. 3A may be implemented by fingerprintimage format module 204. Furthermore, the steps of FIG. 3A do notnecessarily have to occur in the order shown, as will be apparent topersons skilled in the relevant art(s) based on the teachings herein.Other structural embodiments will be apparent to persons skilled in therelevant art(s) based on the discussion contained herein. These stepsare described in detail below.

The process begins with step 302. In step 302, system variables areinitialized. Control then passes to step 304.

In step 304, the start of a fingerprint roll is detected. Control thenpasses to step 306.

In step 306, a plurality of fingerprint image frames are captured.Control then passes to step 308.

In step 308, a centroid window corresponding to each of the plurality ofcaptured fingerprint image frames is determined. Control then passes tostep 310.

In step 310, pixels of the determined centroid windows are knitted intoan overall fingerprint image. Control then passes to step 312.

In step 312, the end of a fingerprint roll is detected. The algorithmthen ends.

More detailed structural and operational embodiments for implementingthe steps of FIG. 3A are described below. These embodiments are providedfor purposes of illustration, and are not intended to limit theinvention. Alternate embodiments, differing slightly or substantiallyfrom those described herein, will be apparent to persons skilled in therelevant art(s) based on the teachings contained herein.

System Variable Initialization

In step 302, variables used by the routine steps must be initializedbefore the process proceeds. In a preferred embodiment, theinitialization phase resets at least the variables shown in Table 1:

TABLE 1 System Variables Variable Variable name type Brief DescriptionRollInitialized boolean indicates whether a fingerprint roll isinitialized RollDetected boolean indicates whether a fingerprint roll isdetected StartRollSensitivity short integer determines sensitivity fordetecting a start of a fingerprint roll StopRollSensitivity shortinteger determines sensitivity for detecting a stop of a fingerprintroll CurrentBits array of currently captured fingerprint frame pixelsPreviousBits array of previously captured fingerprint pixels frameImageBits array of composite fingerprint frame pixels

Both RollInitialized and RollDetected are initially set to FALSE. When aroll is initialized, RollInitialized is set to TRUE. When a roll isdetected, RollDetected is set to TRUE. When a roll is complete, bothvariables are set to FALSE.

StartRollSensitivity and StopRollSensitivity may be fixed or adjustablevalues. In an embodiment, the StartRollSensitivity andStopRollSensitivity variables may be configured from a user interface tocontrol the sensitivity of the rolling process. In an embodiment, thesevariables can take values between 0 and 100 representing low sensitivityto high sensitivity. Other value ranges may be used, as would berecognized by persons skilled in the relevant art(s).

CurrentBits, PreviousBits, and ImageBits are comprised of arrays ofpixels, with each pixel having a corresponding intensity. In a preferredembodiment, all pixel intensity values in CurrentBits, PreviousBits, andImageBits are set to 255 (base 10), which corresponds to white. Zero (0)corresponds to black. Pixel values in between 0 and 255 correspond toshades of gray, becoming lighter when approaching 255 from 0. Thisscheme may be chosen in keeping with the concept that a fingerprintimage contains black ridges against a white background. Other pixelintensity value ranges may be used, as would be recognized by personsskilled in the relevant art(s). Furthermore, the invention is fullyapplicable to the use of a color fingerprint scanner, with colored pixelvalues, as would be recognized by persons skilled in the relevantart(s).

Detecting Start of Fingerprint Roll

In step 304, the start of a fingerprint roll is detected. Before arolled fingerprint image can begin to be created, the system must detectthat the user has placed a finger in or against the fingerprint imagecapturing area of fingerprint scanner 102 (shown in FIG. 1), and isbeginning to roll the finger.

In a preferred embodiment, a method for detecting a finger onfingerprint scanner 102 is based on calculating a percentage intensitychange from a previously captured fingerprint scanner image(PreviousBits) to a currently captured fingerprint scanner image(CurrentBits). Each pixel in CurrentBits may be compared to thecorresponding, identically located pixel in PreviousBits. If thedifference in the intensities of a compared pixel pair is greater than apredetermined threshold, that pixel pair is counted as being different.Once all pixels have been compared, the percentage of different pixelsis calculated. In alternate embodiments, the number of different pixelsmay be calculated without determining a percentage. This calculatedpixel difference percentage is used to determine when a roll has startedand stopped. When the algorithm is initiated, this calculated percentagewill be relatively low since virtually no pixels will be different.

FIG. 4 shows an example captured image frame 402. Captured image frame402 is substantially light or white, because no finger was present inthe image capturing area of fingerprint scanner 102 when the frame wascaptured. Fingerprint image frames captured when no finger is presentwill have an overall lighter intensity value relative to when a fingeris present.

FIG. 5 shows an example captured fingerprint image frame 502 with afingerprint image 504 present. Fingerprint image 504 represents theportion of a finger in contact with the fingerprint scanner imagecapturing area or surface. Because a fingerprint image 504 was captured,captured fingerprint image frame 502 will have an overall darkerintensity value relative to captured image frame 402 (shown in FIG. 4).Hence, an increase in the calculated pixel difference percentage willoccur after placing a finger in the image capturing area of afingerprint scanner.

Once the calculated pixel difference percentage goes beyond apredetermined start roll sensitivity threshold value(StartRollSensitivity), the algorithm goes into rolling mode. As soon asthe percentage goes below a predetermined stop roll sensitivitythreshold value (StopRollSensitivity), the algorithm exits rolling mode(discussed in greater detail below). As discussed above, in alternateembodiments, the number of different pixels may be calculated, withoutdetermining a percentage, and this number may be compared to apredetermined stop roll sensitivity threshold value.

FIG. 3B provides a flowchart illustrating example steps for implementingstep 304.

In step 314, a pixel intensity difference percentage value between acurrent fingerprint image frame and a previous fingerprint image frameis generated. In an alternate embodiment, a pixel intensity differencecount value between a current fingerprint image frame and a previousfingerprint image frame may be generated. Control then proceeds to step316.

In step 316, whether the generated pixel intensity difference percentagevalue is greater than a start roll sensitivity threshold percentagevalue is determined. In the alternate embodiment stated in step 314above, whether a generated pixel difference count value is greater thana start roll sensitivity threshold value may be determined.

FIG. 3C provides a flowchart illustrating example steps for implementingan embodiment of step 316.

In step 318, a current fingerprint image frame is captured. Control thenproceeds to step 320.

In step 320, the intensity of each pixel of the current fingerprintimage frame is compared to the intensity of a corresponding pixel of apreviously captured fingerprint image frame to obtain a pixel intensitydifference count value. In embodiments, compared pixels are founddifferent if their respective pixel intensity values are not the same.In alternative embodiments, compared pixels may be found different iftheir intensity values differ by greater than a pixel intensitydifference threshold. The pixel intensity difference threshold may beestablished as a system variable, and may be set to a fixed value, ormay be adjustable by a user. Control then proceeds to step 322.

In step 322, a pixel intensity difference percentage value iscalculated. In an alternate embodiment, a pixel difference count valuemay be calculated.

In the following example of a preferred embodiment, a finger detectedfunction (FingerDetected) is presented. This function may be called todetect whether a finger is present on a fingerprint scanner.

BOOL  FingerDetected(void) { double dDiff; double dDiffThreshold; short  nPixelThreshold; dDiffThreshold  = ((100 − m_nRollStartSensitivity) *0.08 / 100); nPixelThreshold = 20; // calculate percentage change fromprevious DIB dDiff = FrameDifference((LPBITMAPINFO)&m_bmihPrevious,(LPBITMAPINFO)&m_bmih, nPixelThreshold); if (dDiff > dDiffThreshold) {return TRUE; } else { return FALSE; } }

In this preferred embodiment, the finger detected function calls a framedifference function. The frame difference routine calculates thepercentage difference between two frames. This difference is calculateddown to the pixel level. Two pixels are considered to be different istheir values are more than a certain value (nDiff) apart. In thefollowing example of a preferred embodiment, a frame difference function(FrameDifference) is presented.

double FrameDifference(LPBITMAPINFO lpBMInfo1, LPBITMAPINFO lpBMInfo2,short nDiff) { // this method compares two frames and returns thepercentage of pixels // that are different. Two pixels are different ifthey differ by // more than nDiff LPBYTE lpBits1; LPBYTE lpBits2; doubledPercentage; long ISize; long ICount; short nBytesPerPixel; // make surethat the bitmaps are the same size If (lpBMInfo1−>bmiHeader.biBitCount!= lpBMInfo2−>bmiHeader.biBitCount ∥ lpBMInfo1−>bmiHeader.biWidth !=lpBMInfo2−>bmiHeader.biWidth ∥ lpBMInfo1−>bmiHeader.biHeight !=lpBMInfo2−>bmiHeader.biHeight) { // bitmaps are 100% different sincethey are not // the same size return 1.0; } lpBits1 =(LPBYTE)lpBMInfo1 + sizeof(BITMAPINFOHEADER) + (8 ==lpBMInfo1−>bmiHeader.biBitCount ? 1024 : 0); lpBits2 =(LPBYTE)lpBMInfo2 + sizeof(BITMAPINFOHEADER) + (8 ==lpBMInfo2−>bmiHeader.biBitCount ? 1024 : 0); nBytesPerPixel =lpBMInfo1−>bmiHeader.biBitCount / 8; if (lpBMInfo1−>bmiHeader.biBitCount% 8) { nBytesPerPixel++; } ISize = IpBMInfol−>bmiHeader.biWidth *IpBMInfo1−>bmiHeader.biHeight * nBytesPerPixel; ICount = 0; for (longlIndex = 0; lIndex < ISize; lIndex++) { if(abs(lpBits1[lIndex] −lpBits2[lIndex]) > nDiff) { ICount++; } } dPercentage = ICount /(double)lSize; return dPercentage; }

In embodiments, fingerprint roll detector module 216 of FIG. 2B maycomprise one or both of the FingerDetected and FrameDifference functionsor hardware equivalents. Fingerprint roll start detector module 222 ofFIG. 2C may comprise one or both of the FingerDetected andFrameDifference functions or hardware equivalents. Furthermore, whenpresent, frame difference detector module 226 of FIG. 2E may compriseone or both of the FingerDetected and FrameDifference functions orhardware equivalents.

Capturing Fingerprint Image Frames

Returning to FIG. 3A, in step 306, a plurality of fingerprint imageframes are captured. Fingerprint image frames are captured from thefingerprint image area of fingerprint scanner 102. As discussed above,in an embodiment, a currently captured fingerprint image frame is storedin CurrentBits, and a previously captured fingerprint image frame isstored in PreviousBits. Portions of these arrays are combined insubsequent steps to form a composite fingerprint image. Portions of oneor both of the fingerprint image frames that were used to detect thestart of a fingerprint roll may also be used to form at least a portionof the composite fingerprint image.

Determining a Centroid Window

In step 308, a centroid window corresponding to each of the plurality ofcaptured fingerprint image frames is determined. After the algorithm hasdetected that a fingerprint roll has started, the task of combiningpixels from captured fingerprint image frames into a composite rolledfingerprint image begins. However, all of the pixels in a particularframe are not necessarily read. Only those pixels inside a particularwindow, the “centroid window,” are read. A centroid window comprisescaptured fingerprint image pixels, substantially trimming off thenon-relevant pixels of a captured fingerprint image frame. By focusingonly on the relevant portion of the captured frame, the processing ofthe captured frame can proceed much faster.

In an embodiment, to determine a centroid window, the leading andtrailing edges of the fingerprint image in a captured fingerprint imageframe are found. These edges are determined by sampling a thin strip ofpixels in a pixel window across the center of a fingerprint frame. FIG.6 shows an example captured fingerprint image frame 602 with afingerprint image 604 and a pixel window 606 present. Pixel window 606is shown across the center of captured fingerprint image frame 602. Thisgenerated pixel window is analyzed to determine the leading and trailingedges of fingerprint image 604. A centroid window is then generatedwithin the leading and trailing edges in fingerprint image frame 602. Anexample centroid window 608 is shown in captured fingerprint image frame602.

FIG. 7A shows a close-up view of an example pixel window 702. Pixelwindow 702 has a vertical pixel height of ten pixels. Pixels in pixelwindow 702 have two possible intensity values of 1 (light) or 0 (dark).These pixel height and intensity values for pixel window 702 arepresented for illustrative purposes, and do not limit the invention. Awide range of these attributes for example pixel window 702 arepossible, as would be known to persons skilled in the relevant art(s)from the teachings herein. For instance, in a fingerprint image framewhere an average fingerprint ridge is five pixels high, a pixel window702 of a height of twenty pixels be effectively used, fitting fourfingerprint ridges within the window on average.

Furthermore, in alternative embodiments, more than one pixel window 702may be generated to determine a centroid window. For example, threepixel windows may be generated within the fingerprint image frame, withpixel windows generated across the center, at or near the top, and at ornear the bottom of the fingerprint image frame. Generating more than onepixel window may provide advantages in locating a fingerprint imagewithin a fingerprint image frame, particularly if the fingerprint imageis off-center.

A histogram is built from the generated pixel window. The histogramincludes the total pixel intensity value for each column of pixels inpixel window 606. An example histogram 704 is shown graphically in FIG.7B. Histogram 704 was built from pixel window 702 of FIG. 7A. Histogram704 includes the total pixel intensity value for each column of pixelsin example pixel window 702. For example, pixel column 706 of pixelwindow 702 has a total pixel intensity value of four, as indicated inhistogram 704. Pixel columns 708 and 710 have respective total pixelintensity values of five and zero, as indicated in histogram 704.

To find the leading edge of a fingerprint image, the algorithm scans thehistogram in the direction opposite of the direction of the fingerprintroll. The algorithm searches for a difference above a predeterminedthreshold between two adjacent columns. Where the total pixel intensitychanges above the threshold value between columns, becoming darker, theleading edge is found. To find the trailing edge of the fingerprint, thealgorithm scans the histogram in the direction of the fingerprint roll,in a similar fashion to finding the leading edge. The “x” coordinates ofthe leading and trailing edges of the histogram become the “x”coordinates of the leading and trailing edges of the centroid window.

In the example of FIGS. 7A and 7B, the leading edge of a fingerprintimage may be found by scanning the histogram from right to left. Whenthe predetermined threshold value is equal to four, for example,scanning the histogram will find a leading edge between pixel columns708 and 710. In an embodiment, any column relative to a determined edgemay be selected as a leading or trailing edge column. Additionally, forexample, because column 708 is darker than column 710, column 708 may bechosen as the leading edge column.

FIG. 3D provides a flowchart illustrating example steps for implementingstep 308 of FIG. 3A.

In step 324, a pixel window in a captured fingerprint image frame isgenerated. Control then proceeds to step 326.

In step 326, a leading edge column and a trailing edge column of afingerprint image are found in the corresponding generated pixel window.Control then proceeds to step 328.

In step 328, a centroid window in the captured fingerprint image framebounded by the leading edge column found and the trailing edge columnfound is generated.

In a preferred embodiment, the window generated in step 328 is centeredin an axis perpendicular to the direction that a finger is rolled. Insuch an embodiment, the generated window may include columns of a heightof a predetermined number of pixels in the axis perpendicular to thedirection that the finger is rolled. Furthermore, the generated windowmay have a length in an axis parallel to the direction that the fingeris rolled equal to the number of pixels spanning the capturedfingerprint image frame along that axis.

FIG. 3E provides a flowchart illustrating example steps for implementingstep 326 of FIG. 3D.

In step 330, a histogram representative of the cumulative pixelintensity of pixels present in each column of the generated window isbuilt. Control then proceeds to step 332.

In step 332, the histogram is scanned in the direction opposite of thatin which the finger is rolled. The algorithm scans for a difference inthe pixel intensities of adjacent columns of the generated window thatis greater than a first fingerprint edge. In an embodiment, the darkercolumn of the adjacent columns is designated the leading edge column. Inalternative embodiments, other columns, such as the other adjacentcolumn, may be designated as the leading edge column. Control thenproceeds to step 334.

In step 334, the histogram is scanned in the direction in which thefinger is rolled for a difference in the pixel intensities of twoadjacent columns that is greater than a second fingerprint edgethreshold. In an embodiment, the darker column of the adjacent columnsis designated the trailing edge column. In alternative embodiments,other columns, such as the other adjacent column, may be designated asthe trailing edge column.

In the following example of a preferred embodiment, a find centroidfunction (FindCentroid) is presented. The FindCentroid function may becalled to determine a centroid window. The function builds a histogramfrom a generated pixel window in a captured fingerprint image frame, andsearches from left to right and then right to left through thehistogram, looking for the edges of a fingerprint.

BOOL FindCentroid(short * pnLeft, short * pnRight) { LPBITMAPINFOlpBMInfo; LPBYTE lpCurrentBits; long * plHistogram; long lIndex; shortnBytesPerPixel; const short cnEdgeThreshold = 64; const short cnCushion= 20; short nLeft; short nRight; short nTop; short nBottom; BOOLbFoundLeft = FALSE; BOOL bFoundRight = FALSE; lpBMInfo =(LPBITMAPINFO)&m_bmih; lpCurrentBits = (LPBYTE)lpBMInfo +sizeof(BITMAPINFOHEADER) + (8 == lpBMInfo−>bmiHeader.biBitCount ? 1024 :0); nBytesPerPixel = lpBMInfo−>bmiHeader.biBitCount / 8; if(lpBMInfo−>bmiHeader.biBitCount % 8) { nBytesPerPixel++; } // boundscheck on acquisition parameters nTop = lpBMInfo−>bmiHeader.biHeight / 2− 10; nBottom = lpBMInfo−>bmiHeader.biHeight / 2 + 10; if (nTop < 0) {nTop = 0; } if (nBottom > lpBMInfo−>bmiHeader.biHeight) { nBottom =lpBMInfo−>bmiHeader.biHeight; } nLeft = 0; nRight =lpBMInfo−>bmiHeader.biWidth; // build the histogram plHistogram = newlong [lpBMInfo−>bmiHeader.biWidth]; memset(plHistogram, 0,lpBMInfo−>bmiHeader.biWidth * sizeof(long)); for (short nHeight = nTop;nHeight < nBottom; nHeight++) { for (short nWidth = nLeft; nWidth <nRight; nWidth++) { for (short nByte = 0; nByte < nBytesPerPixel;nByte++) { lIndex = nHeight * lpBMInfo−>bmiHeader.biWidth *nBytesPerPixel + nWidth * nBytesPerPixel + nByte; plHistogram[nWidth]  = plHistogram[nWidth] + lpCurrentBits[lIndex]; } } } // find the leftedge for (short nWidth = nLeft + 1; nWidth < nRight; nWidth++) {if(abs(plHistogram[nWidth] − plHistogram[nWidth − 1]) > cnEdgeThreshold){ *pnLeft = nWidth; bFoundLeft = TRUE; break; } } if (bFoundLeft) { //find the right edge for (short nWidth = nRight − 1; nWidth > *pnLeft;nWidth−−) { if (abs(plHistogram[nWidth] − plHistogram[nWidth − 1]) >cnEdgeThreshold) { *pnRight = rtWidth; bFoundRight = TRUE; break; } } }// give the centroid some cushion *pnLeft −= cnCushion; *pnRight     +=cnCushion; If(*pnLeft < 0) { *pnLeft = 0; } if (*pnRight >lpBMInfo−>bmiHeader.biWidth) { *pnRight = lpBMInfo−>bmiHeader.biWidth; }delete [ ]plHistogram; return bFoundLeft && bFoundRight; }

In an embodiment, centroid window determiner module 218 of FIG. 2B mayimplement the FindCentroid function or hardware equivalent.

Knitting Pixels

Returning to FIG. 3A, in step 310, pixels of each determined centroidwindow are knitted into an overall fingerprint image. Only pixels withinthe determined centroid window are considered for knitting. This has theadvantage of increasing the speed of the knitting process. The centroidwindow provides an indication of where the finger is currently locatedon the fingerprint scanner. Therefore, it is not necessary to copy orknit pixels that are outside of this window.

In a preferred embodiment, the copying of pixels for knitting is aconditional copy based on the intensity, or darkness, of the pixel. Inother words, the algorithm for copying pixels from the centroid windowis not a blind copy. The algorithm compares each pixel of the ImageBitsarray with the corresponding pixel of the CurrentBits array. A pixelwill only be copied from CurrentBits if the pixel is darker than thecorresponding pixel of ImageBits. This rule prevents the image frombecoming too blurry during the capture process. This entire process isreferred to herein as “knitting.”

FIG. 8 shows an example of pixel knitting for an example segment of acomposite fingerprint image. Segment 802 is a three pixel by three pixelsegment of a current fingerprint centroid (i.e., CurrentBits). Segment804 is a three pixel by three pixel segment of a composite fingerprintimage (i.e., ImageBits). Segments 802 and 804 each include nine pixels.The intensity values of these pixels are shown. Each pixel of segment802 is compared to the corresponding pixel of segment 804. The pixel ofsegment 804 is replaced by the corresponding pixel of segment 802 if thepixel of segment 802 has a darker intensity value (e.g. a lowerintensity value). A resulting knitted composite fingerprint imagesegment 806 is created.

For example, pixel 808 has an intensity value of 94. Pixel 808 iscompared against pixel 810, which has an intensity value of 118. Becausethe intensity value of pixel 808 is darker than that of pixel 810 (i.e.,94 is a lower intensity value than 118), the intensity value of pixel812 is set to the new pixel intensity value of pixel 808. Likewise,pixel 814 has an intensity value of 123. Pixel 814 is compared againstpixel 816, which has an intensity value of 54. Because the intensityvalue of pixel 816 is darker than that of pixel 814 (i.e., 54 is a lowerintensity value than 123), the intensity value of pixel 818 remains thatof pixel 816.

FIG. 3F provides a flowchart illustrating example steps for implementingstep 310 of FIG. 3A.

In step 336, the intensity of each pixel of the determined centroidwindow is compared to the intensity of the corresponding pixel of anoverall fingerprint image. Control then proceeds to step 338.

In step 338, the pixel of the composite fingerprint image is replacedwith the corresponding pixel of the determined centroid window if thepixel of the determined centroid window is darker than the correspondingpixel of the composite fingerprint image.

In the following example of a preferred embodiment, a pixel knittingfunction (CopyConditionalBits) is presented. The CopyConditionalBitsfunction copies pixels from the determined centroid window (CurrentBits)into the overall image (ImageBits). The function does not blindly copythe pixels. Instead, the function will only copy a pixel if the newvalue is less than the previous value.

void ConditionalCopyBits(short nLeft, short nRight) { LPBITMAPINFOlpBMInfo; LPBYTE lpCaptureBits; long lIndex; short nBytesPerPixel;lpBMInfo = (LPBITMAPINFO)&m_bmih; lpCaptureBits = (LPBYTE)lpBMInfo +sizeof(BITMAPINFOHEADER) + (8 == lpBMInfo−>bmiHeader.biBitCount ? 1024 :0); nBytesPerPixel = lpBMInfo−>bmiHeader.biBitCount / 8;if(lpBMInfo−>bmiHeader.biBitCount % 8) { nBytesPerPixel++; } // copypixels from capture window only if less than previous for (short nHeight= 0; nHeight < lpBMInfo−>bmiHeader.biHeight; nHeight++) { for (shortnWidth = nLeft; nWidth < nRight; nWidth++) { for (short nByte = 0; nByte< nBytesPerPixel; nByte++) { lIndex = nHeight *lpBMInfo−>bmiHeader.biWidth * nBytesPerPixel + nWidth * nBytesPerPixel +nByte; // only copy if the new value is less than the previous if(m_lpRollBits[lIndex] > lpCaptureBits[lIndex]) { m_lpRollBits[lIndex] =lpCaptureBits[lIndex]; } } } } // end for }

In an embodiment of the present invention, pixel knitting module 220 ofFIG. 2B may implement the CopyConditionalBits function or hardwareequivalent.

Detecting End of Fingerprint Roll

Returning to FIG. 3A, in step 312, the end of a fingerprint roll isdetected. After a fingerprint roll is complete, the user will removetheir finger from the fingerprint scanner image capturing area. Thesystem detects that the user has removed their finger, and ends therolled fingerprint capturing algorithm. At this point, an overall rolledfingerprint image has been generated. FIG. 9 shows an example of anoverall rolled fingerprint image 902, displayed in a rolled fingerprintdisplay panel 904. Overall rolled fingerprint image 902 of FIG. 9 is acomposite image, generated according to the present invention.

Returning to FIG. 3A, step 312 operates substantially similar to step304, where the start of a fingerprint roll is detected. As discussedabove, in a preferred embodiment, a method for detecting a finger onfingerprint scanner 102 is based on a percentage change from apreviously captured fingerprint image (PreviousBits) to a currentlycaptured fingerprint image (CurrentBits). Each pixel in CurrentBits iscompared against the corresponding, identically located pixel inPreviousBits. If the difference in the intensities of a compared pixelpair is greater than a predetermined threshold, that pixel pair iscounted as being different. Once all pixels have been compared, thepercentage of different pixels is calculated. In alternate embodiments,the number of different pixels is calculated without determining apercentage.

As discussed above, this calculated pixel difference percentage is usedto determine when a roll has started and stopped. When the rolledfingerprint capture algorithm is operating, and a fingerprint is beingcaptured, this percentage will be relatively low because a relativelysmall number of pixels will be changing during the roll. However, whenthe user removes their finger from the scanner surface, the differencepercentage will increase, as fingerprint image data is no longer beingcaptured.

As discussed above, as soon as the percentage goes below a predeterminedstop roll sensitivity threshold value (StopRollSensitivity), thealgorithm exits rolled fingerprint capture mode.

FIG. 3G provides a flowchart illustrating example steps for implementingstep 312 of FIG. 3A.

In step 340, a pixel intensity difference percentage value between acurrent fingerprint image frame and a previous fingerprint image frameis generated. In an alternative embodiment, a pixel intensity differencecount value between a current fingerprint image frame and a previousfingerprint image frame may be generated. Control then proceeds to step342.

In step 342, whether the generated pixel intensity difference percentagevalue is less than a stop roll sensitivity threshold percentage value isdetermined. In the alternate embodiment mentioned in step 340, whether agenerated pixel intensity difference count value is greater than a stoproll sensitivity threshold value may be determined.

FIG. 3C provides a flowchart illustrating example steps for implementingan embodiment of step 340, and is described in more detail above inreference to step 304 of FIG. 3A.

A finger detected function (FingerDetected) is presented above inreference to step 304 of FIG. 3A. This function may be called to detectwhether a finger is present on a fingerprint scanner. Refer to thesection above for a more detailed description of this function.Furthermore, a frame difference function (FrameDifference) is alsopresented above in reference to step 304 of FIG. 3A. This function maybe called to calculate the percentage difference between two frames.Refer to the section above for a more detailed description of thisfunction.

In embodiments, fingerprint roll stop detector module 224 of FIG. 2C maycomprise one or both of the FingerDetected and FrameDifference functionsdescribed above or hardware equivalents.

Rolled Fingerprint Display Panel

In an embodiment, rolled fingerprint display panel 904 of FIG. 9 is anexample display panel that allows a user to input rolled fingerprintcapture parameters, to begin a roll, and to view fingerprint images,among other functions. Some of these functions may include: indicatingwhen a finger is present on the fingerprint scanner; permitting a userto select a roll speed for setting a fingerprint image capturing areasampling interval; permitting a user to select a start sensitivitythreshold value for detecting a start of a fingerprint roll; permittinga user to select a stop sensitivity threshold value for detecting a stopof a fingerprint roll; permitting a user to select a guided roll mode;permitting a user to activate a roll mode; permitting a user tofreeze/unfreeze a rolled fingerprint image; permitting a user to save anoverall fingerprint image; permitting a user to alter the videoproperties of the fingerprint scanner; and permitting a user to exit therolled fingerprint capture algorithm.

Example Computer System

An example of a computer system 104 is shown in FIG. 10. The computersystem 104 represents any single or multi-processor computer.Single-threaded and multi-threaded computers can be used. Unified ordistributed memory systems can be used.

The computer system 104 includes one or more processors, such asprocessor 1004. One or more processors 1004 can execute softwareimplementing the routine shown in FIG. 3A as described above. Eachprocessor 1004 is connected to a communication infrastructure 1002(e.g., a communications bus, cross-bar, or network). Various softwareembodiments are described in terms of this exemplary computer system.After reading this description, it will become apparent to a personskilled in the relevant art how to implement the invention using othercomputer systems and/or computer architectures.

Computer system 104 may include a graphics subsystem 1003 (optional).Graphics subsystem 1003 can be any type of graphics system supportingcomputer graphics. Graphics subsystem 1003 can be implemented as one ormore processor chips. The graphics subsystem 1003 can be included as aseparate graphics engine or processor, or as part of processor 1004.Graphics data is output from the graphics subsystem 1003 to bus 1002.Display interface 1005 forwards graphics data from the bus 1002 fordisplay on the display unit 106.

Computer system 104 also includes a main memory 1008, preferably randomaccess memory (RAM), and can also include a secondary memory 1010. Thesecondary memory 1010 can include, for example, a hard disk drive 1012and/or a removable storage drive 1014, representing a floppy disk drive,a magnetic tape drive, an optical disk drive, etc. The removable storagedrive 1014 reads from and/or writes to a removable storage unit 1018 ina well known manner. Removable storage unit 1018 represents a floppydisk, magnetic tape, optical disk, etc., which is read by and written toby removable storage drive 1014. As will be appreciated, the removablestorage unit 1018 includes a computer usable storage medium havingstored therein computer software and/or data.

In alternative embodiments, secondary memory 1010 may include othersimilar means for allowing computer programs or other instructions to beloaded into computer system 104. Such means can include, for example, aremovable storage unit 1022 and an interface 1020. Examples can includea program cartridge and cartridge interface (such as that found in videogame devices), a removable memory chip (such as an EPROM, or PROM) andassociated socket, and other removable storage units 1022 and interfaces1020 which allow software and data to be transferred from the removablestorage unit 1022 to computer system 104.

Computer system 104 can also include a communications interface 1024.Communications interface 1024 allows software and data to be transferredbetween computer system 104 and external devices via communications path1026. Examples of communications interface 1024 can include a modem, anetwork interface (such as Ethernet card), a communications port, etc.Software and data transferred via communications interface 1024 are inthe form of signals which can be electronic, electromagnetic, optical orother signals capable of being received by communications interface1024, via communications path 1026. Note that communications interface1024 provides a means by which computer system 104 can interface to anetwork such as the Internet.

Graphical user interface module 1030 transfers user inputs fromperipheral devices 1032 to bus 1002. In an embodiment, one or moreperipheral devices 1032 may be fingerprint scanner 102. These peripheraldevices 1032 also can be a mouse, keyboard, touch screen, microphone,joystick, stylus, light pen, voice recognition unit, or any other typeof peripheral unit.

The present invention can be implemented using software running (thatis, executing) in an environment similar to that described above withrespect to FIG. 10. In this document, the term “computer programproduct” is used to generally refer to removable storage unit 1018, ahard disk installed in hard disk drive 1012, or a carrier wave or othersignal carrying software over a communication path 1026 (wireless linkor cable) to communication interface 1024. A computer useable medium caninclude magnetic media, optical media, or other recordable media, ormedia that transmits a carrier wave. These computer program products aremeans for providing software to computer system 104.

Computer programs (also called computer control logic) are stored inmain memory 1008 and/or secondary memory 1010. Computer programs canalso be received via communications interface 1024. Such computerprograms, when executed, enable the computer system 104 to perform thefeatures of the present invention as discussed herein. In particular,the computer programs, when executed, enable the processor 1004 toperform the features of the present invention. Accordingly, suchcomputer programs represent controllers of the computer system 104.

In an embodiment where the invention is implemented using software, thesoftware may be stored in a computer program product and loaded intocomputer system 104 using removable storage drive 1014, hard drive 1012,or communications interface 1024. Alternatively, the computer programproduct may be downloaded to computer system 104 over communicationspath 1026. The control logic (software), when executed by the one ormore processors 1004, causes the processor(s) 1004 to perform thefunctions of the invention as described herein.

In another embodiment, the invention is implemented primarily infirmware and/or hardware using, for example, hardware components such asapplication specific integrated circuits (ASICs). Implementation of ahardware state machine so as to perform the functions described hereinwill be apparent to persons skilled in the relevant art(s).

CONCLUSION

While various embodiments of the present invention have been describedabove, it should be understood that they have been presented by way ofexample only, and not limitation. It will be apparent to persons skilledin the relevant art that various changes in form and detail can be madetherein without departing from the spirit and scope of the invention.Thus, the breadth and scope of the present invention should not belimited by any of the above-described exemplary embodiments, but shouldbe defined only in accordance with the following claims and theirequivalents.

1. A method for rolled fingerprint capture, comprising the steps of: (1)detecting the start of a fingerprint roll; (2) capturing a plurality offingerprint image frames; (3) determining a centroid windowcorresponding to each of the plurality of captured fingerprint imageframes, including the steps of: (a) generating a pixel window in acaptured fingerprint image frame; (b) finding a leading edge column anda trailing edge column of a fingerprint image in the correspondinggenerated pixel window, including the steps of: (i) building a histogramrepresentative of the cumulative pixel intensity of pixels present ineach column of the generated window; (ii) scanning through the histogramin the direction opposite that in which the finger is rolled for adifference in the total pixel intensities of first adjacent columns ofthe generated pixel window that is greater than a first fingerprint edgethreshold to find a leading edge; and (iii) scanning through thehistogram in the direction in which the finger is rolled for adifference in the total pixel intensities of second adjacent columns ofthe generated pixel window that is greater than a second fingerprintedge threshold to find a trailing edge; and (c) generating the centroidwindow in the captured fingerprint image frame, wherein the centroidwindow is bounded by the leading edge column found and the trailing edgecolumn found; (4) knitting pixels of each determined centroid windowinto a composite fingerprint image; and (5) detecting the end of saidfingerprint roll.
 2. The method of claim 1, further comprising the stepsof: (iv) selecting the column of darker total pixel intensity of thefirst adjacent columns as the leading edge column; and (v) selecting thecolumn of darker total pixel intensity of the second adjacent columns asthe trailing edge column.
 3. An apparatus for rolled fingerprintcapture, comprising: a fingerprint scanner; a computer system coupled tosaid fingerprint scanner, wherein said computer system comprises arolled fingerprint capture module; and a display that displays acomposite fingerprint image generated by said rolled fingerprint capturemodule, wherein said rolled fingerprint capture module determines acentroid window corresponding to each of a plurality of fingerprintimage frames captured by said fingerprint scanner and knits pixels ofeach said determined centroid window into a composite fingerprint image;wherein in each of said plurality of fingerprint image frames, saidrolled fingerprint capture module generates a pixel window; wherein saidrolled fingerprint capture module comprises a histogram builder; whereinfor each said generated pixel window, said histogram builder builds ahistogram representative of the cumulative pixel intensity of pixelspresent in each column of said generated pixel window; wherein for eachsaid histogram, said rolled fingerprint capture module scans throughsaid histogram in the direction opposite that in which the finger isrolled for a difference in the total pixel intensities of first adjacentcolumns of the generated pixel window that is greater than a firstfingerprint edge threshold to find a leading edge column; wherein foreach said histogram, said rolled fingerprint capture module scansthrough said histogram in the direction in which the finger is rolledfor a difference in the total pixel intensities of second adjacentcolumns of the generated pixel window that is greater than a secondfingerprint edge threshold to find a trailing edge column; and whereinsaid rolled fingerprint capture module generates said determinedcentroid window in said each of said plurality of fingerprint imageframe, wherein said each determined centroid window is bounded by thecorresponding said leading edge column and the corresponding saidtrailing edge column.
 4. The apparatus of claim 3, further comprising acommunications interface signal coupled to said computer system.
 5. Theapparatus of claim 3, wherein said computer system comprises: a centroidwindow determiner module.
 6. The apparatus of claim 3, wherein saidrolled fingerprint capture module comprises: a pixel knitting modulethat compares the intensity of each pixel of said each determinedcentroid window to the intensity of a corresponding pixel of saidcomposite fingerprint image and replaces said corresponding pixel ofsaid composite fingerprint image with said pixel of said each determinedcentroid window if said pixel of said each determined centroid window isdarker than said corresponding pixel of said composite fingerprintimage.
 7. The apparatus of claim 3, wherein said computer systemcomprises: a fingerprint roll detector module.
 8. The apparatus of claim7, wherein said fingerprint roll detector module comprises: afingerprint roll start detector module; and a fingerprint roll stopdetector module.
 9. The apparatus of claim 3, wherein said rolledfingerprint capture module comprises: a fingerprint capture module; afingerprint image format module coupled to said fingerprint capturemodule; and a fingerprint image display module coupled to saidfingerprint image format module.
 10. A system for rolled fingerprintcapture, comprising: a fingerprint roll start detector module thatdetects the start of a fingerprint roll in a fingerprint image capturingarea; a centroid window determiner module that determines a centroidwindow corresponding to each of a plurality of captured fingerprintimage frames; a pixel knitting module that knits pixels of said eachdetermined centroid window into a composite fingerprint image; and afingerprint roll stop detector that detects the end of the fingerprintroll; wherein said centroid window determiner module generates a pixelwindow in said each of a plurality of captured fingerprint image frames;wherein said centroid window determiner module comprises a histogrambuilder; wherein for each said generated pixel window, said histogrambuilder builds a histogram representative of the cumulative pixelintensity of pixels present in each column of said generated pixelwindow; wherein for each said histogram, said centroid window determinermodule scans through said histogram in the direction opposite that inwhich the finger is rolled for a difference in the total pixelintensities of first adjacent columns of the generated pixel window thatis greater than a first fingerprint edge threshold to find a leadingedge column; wherein for each said histogram, said centroid windowdeterminer module scans through said histogram in the direction in whichthe finger is rolled for a difference in the total pixel intensities ofsecond adjacent columns of the generated pixel window that is greaterthan a second fingerprint edge threshold to find a trailing edge column;and wherein said centroid window determiner module generates saiddetermined centroid window in said each of a plurality of fingerprintimage frames, wherein said each determined centroid window is bounded bythe corresponding said leading edge column and the corresponding saidtrailing edge column.
 11. The system of claim 10, wherein said pixelknitting module knits pixels of each of said determined centroid windowinto said composite fingerprint image, wherein said pixel knittingmodule compares the intensity of each pixel of said each of saiddetermined centroid window to the intensity of a corresponding pixel ofsaid composite fingerprint image and replaces said corresponding pixelof said composite fingerprint image with said pixel of said each of saiddetermined centroid window if said pixel of said each of said determinedcentroid window is darker than said corresponding pixel of saidcomposite fingerprint page.
 12. A system for rolled fingerprint capture,comprising: means for detecting the start of a fingerprint roll; meansfor capturing a plurality of fingerprint image frames; means fordetermining a centroid window corresponding to each of the plurality ofcaptured fingerprint image frames; means for knitting pixels of eachdetermined centroid window into a composite fingerprint image; and meansfor detecting the end of said fingerprint roll; wherein said determiningmeans includes: means for generating a pixel window in a capturedfingerprint image frame, means for finding a leading edge column and atrailing edge column of a fingerprint image in the correspondinggenerated pixel window, and means for generating the centroid window inthe captured fingerprint image frame, wherein the centroid window isbounded by the leading edge column found and the trailing edge columnfound; wherein said edge finding means comprises: means for building ahistogram representative of the cumulative pixel intensity of pixelspresent in each column of the generated window, means for scanningthrough the histogram in the direction opposite that in which the fingeris rolled for a difference in the total pixel intensities of firstadjacent columns of the generated pixel window that is greater than afirst fingerprint edge threshold to find a leading edge, and means forscanning through the histogram in the direction in which the finger isrolled for a difference in the total pixel intensities of secondadjacent columns of the generated pixel window that is greater than asecond fingerprint edge threshold to find a trailing edge.
 13. Acomputer program product comprising a computer useable medium havingcomputer program logic recorded thereon for enabling a processor in acomputer system to permit a user to capture a rolled fingerprint, saidcomputer program logic comprising: means for enabling the processor todetect the start of a fingerprint roll; means for enabling the processorto capture a plurality of fingerprint image frames; means for enablingthe processor to determine a centroid window corresponding to each ofthe plurality of captured fingerprint image frames; means for enablingthe processor to knit pixels of each determined centroid window into acomposite fingerprint image; and means for enabling the processor todetect the end of said fingerprint roll; wherein said means for enablingthe processor to determine a centroid window comprises: means forenabling a processor to generate a pixel window in a capturedfingerprint image frame, means for enabling a processor to find aleading edge column and a trailing edge column of a fingerprint image inthe corresponding generated pixel window, and means for enabling aprocessor to generate the centroid window in the captured fingerprintimage frame, wherein the centroid window is bounded by the leading edgecolumn found and the trailing edge column found; wherein said means forenabling a processor to find a leading edge column and a trailing edgecolumn comprises: means for enabling a processor to build a histogramrepresentative of the cumulative pixel intensity of pixels present ineach column of the generated window, means for enabling a processor toscan through the histogram in the direction opposite that in which thefinger is rolled for a difference in the total pixel intensities offirst adjacent columns of the generated pixel window that is greaterthan a first fingerprint edge threshold to find a leading edge, andmeans for enabling a processor to scan through the histogram in thedirection in which the finger is rolled for a difference in the totalpixel intensities of second adjacent columns of the generated pixelwindow that is greater than a second fingerprint edge threshold to finda trailing edge.